Financial Optimization ISE 347/447. Preliminaries. Dr. Ted Ralphs

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1 Financial Optimization ISE 347/447 Preliminaries Dr. Ted Ralphs

2 ISE 347/447 Preliminaries 1 Introductory Stuff Welcome! Class Meeting Time Office Hours TBD Surveys

3 ISE 347/447 Preliminaries 2 What will this class be about? Optimization Modeling and Methods Linear and Nonlinear Programming Integer Programming Dynamic Programming Stochastic Programming Financial Applications Asset/Liability Management Option Pricing and Hedging Risk Management Portfolio Optimization Modeling Maguages and Software Excel Solver AMPL Python!

4 ISE 347/447 Preliminaries 3 What do I expect you to know? Undergraduate mathematics A little mathematical modeling A little probability theory

5 ISE 347/447 Preliminaries 4 What are the goals for the course? After this course, you should be able to: Understand the basic optimization methodologies used in financial decision-making. Understand how to formulate financial optimization programs using the tools of mathematical programming. Understand how to select the optimization technique most appropriate for a given financial optimization problem. Understand how to use spreadsheets and modeling languages to interface with optimization software for solving financial optimization problems.

6 ISE 347/447 Preliminaries 5 Approximate Syllabus Category Topic Lectures Introduction Introduction 2 Models and Methods Linear Programming 2 Software Excel Solver and AMPL 2 Application Asset/Liability Management and Asset Pricing 2 Models and Methods Quadratic Programming 2 Software GAMS and software for nonlinear programming 2 Application Portfolio Optimization 2 Models and Methods Integer Programming 2 Application Constructing an Index Fund 2 Models and Methods Dynamic Programming 2 Application Options Pricing 2 Models and Methods Stochastic Programming 2 Software Software for Stochastic Programming 2 Application Portfolio Optimization and Option Pricing 2

7 ISE 347/447 Preliminaries 6 Course Requirements Attendance Participation Reading Homework Exams

8 ISE 347/447 Preliminaries 7 Homework and Final Project There will be approximately 5 problem sets worth 20% of your grade. There will also be two mid-terms, a final project, and a final exam, each worth 20% of your grade. We will try using Google Classroom for turning in assignments and see how that goes. Homework is due at the beginning of Tuesday s class. Lateness policy is in the syllabus. I encourage working together, but you must write up the homework yourself (unless it is a group assignment). Please reference the work of others. Basic problem types: Mathematical Modeling Computation

9 ISE 347/447 Preliminaries 8 Grading Your grade should correspond to your learning and understanding of the course material. We will be randomly grading selected problems. Detailed solutions for selected problems will be distributed. Weighting 20% Homework 20% Midterm (each) 20% Final Project 20% Final Exam

10 ISE 347/447 Preliminaries 9 Class Web Site The class Web site will be at but this will also be supplemented by the Google Classroom site. Slides from the previous time I taught the class are already posted, but they will be updated as I go. All handouts for the class will also be available. There will also be links to other relevant sites and reference materials.

11 ISE 347/447 Preliminaries 10 Textbook The primary text is Cornuejols and Tütüncü. I will also take material out of some other texts. There is an abundance of reference material on the Web. Check the Web site for links. Please let me know if you want additional supplementary material.

12 ISE 347/447 Preliminaries 11 My Approach to Lectures Lectures should be as interactive as possible. You will get more out of this course if you ask questions during lecture. The pace and structure of the lectures can be adjusted. I need feedback from you to adjust appropriately.

13 ISE 347/447 Preliminaries 12 Some More Notes This is only the second time I have taught this course (and the first was a while back), so I will be adjusting as we proceeed. The adjustments will be based on your feedback, so please let me know what you like and don t like. Please pay attention to the policy regarding citing the work of others in the syllabus. I take this policy very seriously.

14 ISE 347/447 Preliminaries 13 Acknowledgements Dr. Raphael Hauser was kind enough to share some of his course materials from a financial optimization course taught at Oxford University: Dr. Jeffrey Linderoth was kind enough to share some of his course materials from a course on stochastic optimization taught at Lehigh: linderot/classes/ie495/

15 ISE 347/447 Preliminaries 14 Questions?